2026
PEEKING INTO THE FUTURE FOR CONTEXTUAL BIASING
ICASSP 2026poster
While end-to-end (E2E) automatic speech recognition (ASR) models excel at general transcription, they struggle to recognize rare or unseen named entities (e.g., contact names, locations), which are critical for downstream applications like virtual assistants. In this paper, we propose a contextual b…